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- Tasks: Develop and scale our core platform while collaborating with financial crime teams.
- Company: Diligent is revolutionising fraud detection for fintechs and banks using AI technology.
- Benefits: Enjoy a dynamic work environment with opportunities for remote work and personal growth.
- Why this job: Make a real impact in the fight against financial crime on a global scale.
- Qualifications: Proficiency in Python, Typescript, React, and AWS Serverless; strong problem-solving skills required.
- Other info: Join a team of ambitious innovators and take ownership of your projects from start to finish.
The predicted salary is between 36000 - 60000 £ per year.
At Diligent, we are on a mission to help fintechs and banks catch fraudulent businesses. We build LLM agents to automate risk investigations during business onboarding and monitoring. For example, we can help investigate the online presence of businesses to detect high-risk activities, identify reputation-compromising signals, comb through news articles to extract new risk insights etc. By turning scattered and unstructured data points into structured, actionable insights, we enable risk teams to make better and faster decisions.
Our founders have built fraud and credit risk models protecting billions in transactions at Europe’s top fintechs, and we’re taking that experience to revolutionize how financial institutions verify the legitimacy of businesses. We already work with leading fintech unicorns and banks, are growing fast and we’re looking for ambitious problem-solvers who are excited about using AI to tackle financial crime at a global scale. If you’re passionate about making a real impact in the fight against fraud, we’d love to have you on our team!
As a Software Engineer at Diligent AI, you’ll be responsible for the development and scaling of our core platform, working closely with enterprise customers, as well as building new zero-to-one initiatives.
- Translate novel LLM capabilities into understandable, intuitive and performant end-user experiences.
- We need someone who has high empathy and is excited by working side-by-side with financial crime teams to solve critical problems.
- Give Diligent AI agents the infrastructure, data sources and tools they need to automate workflows for financial compliance teams.
Technologies: Python, Typescript, React, AWS Serverless
A strong sense of ownership and autonomy is essential - you’ll take full responsibility for your projects from start to finish and you’ll be expected to deal with ambiguity getting things done without overcomplicating solutions.
Interview Process:
- CTO meet-and-greet (30 mins)
- Technical interview (60-90 mins)
- Deepdive interview with Ahmed focusing on problem solving, coding proficiency, systems design and architecture.
- CEO meet-and-greet (30 mins)
Backend Software Engineer - Credit (f/m/d) employer: Diligent (YC W24)
Contact Detail:
Diligent (YC W24) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Backend Software Engineer - Credit (f/m/d)
✨Tip Number 1
Familiarise yourself with the latest trends in AI and financial crime prevention. Understanding how LLMs can be applied in risk investigations will not only impress us but also show your genuine interest in the role.
✨Tip Number 2
Prepare to discuss your experience with Python, Typescript, and AWS Serverless. Be ready to share specific examples of projects where you've used these technologies, as practical knowledge is key for this position.
✨Tip Number 3
Showcase your problem-solving skills during the technical interview. Think aloud while tackling coding challenges, as we value the thought process just as much as the final solution.
✨Tip Number 4
Demonstrate your empathy and collaboration skills. Be prepared to discuss how you've worked alongside teams to address complex issues, especially in high-stakes environments like financial compliance.
We think you need these skills to ace Backend Software Engineer - Credit (f/m/d)
Some tips for your application 🫡
Understand the Company Mission: Familiarise yourself with Diligent's mission to combat financial crime using AI. Highlight your passion for fintech and how your skills align with their goals in your application.
Tailor Your CV: Ensure your CV reflects relevant experience in backend development, particularly with Python, Typescript, and AWS Serverless. Emphasise any projects that demonstrate your ability to work on complex systems and your problem-solving skills.
Craft a Compelling Cover Letter: Write a cover letter that showcases your empathy and enthusiasm for working alongside financial crime teams. Discuss specific examples of how you've tackled challenges in previous roles and how you can contribute to Diligent's mission.
Prepare for Technical Interviews: Anticipate technical questions related to coding proficiency, systems design, and architecture. Brush up on relevant concepts and be ready to discuss your thought process during problem-solving scenarios.
How to prepare for a job interview at Diligent (YC W24)
✨Understand the Company Mission
Before your interview, make sure you understand Diligent's mission to combat financial crime using AI. Familiarise yourself with their products and how they help fintechs and banks. This will show your genuine interest in the role and the company.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, Typescript, React, and AWS Serverless. Have examples ready that demonstrate your coding proficiency and problem-solving skills, especially in relation to building scalable applications.
✨Prepare for Deep-Dive Questions
Expect a technical interview focusing on systems design and architecture. Brush up on your knowledge of software engineering principles and be ready to tackle complex problems. Practice explaining your thought process clearly and concisely.
✨Demonstrate Empathy and Collaboration
Since the role involves working closely with financial crime teams, highlight your ability to empathise with users and collaborate effectively. Share examples of past experiences where you successfully worked alongside others to solve critical issues.
